Token Cost

Summary: Where to Find Astra Not free. Free and Go plans do not include Astra; their default model stays GPT-5.6 Luna. On Plus, Astra does not appear in regular Chat. Access arrives through ChatGPT Work and Codex. On Pro, Business and Enterprise, it shows up in the model picker under the Pro option, labelled GPT-6 Pro. The model underneath is Astra. Enterprise workspaces get it off by default at launch. An admin has to enable it. Codex CLI 0.153.0 or newer is required, and the desktop app needs updating too. In the API the model id is gpt-6-astra: 1.05M token context, 128K output, $10 in / $50 out per million tokens. Our GPT-6 Astra launch write-up covered what the model is, the benchmark table and the price tag. Two days later the question landing in the inbox is a different one: “I pay for Plus, there is no Astra anywhere in my model picker, where is it?” ...

GPT-6 Astra in 30 Seconds GPT-6 Astra is OpenAI’s new flagship, announced on September 3, 2026. The company calls it “the world’s most intelligent and aligned model”. There is no Sol/Terra/Luna split this time. The lineup is Astra and Astra Pro. API pricing is $10 per million input tokens and $50 per million output tokens: 2.5x GPT-5.6 Sol’s promotional price, and identical to Claude Fable 5.1. The scores are high but footnoted. The headline 98.6% on ARC-AGI-3 came from a custom harness; the same model scores 62.7% on the standard one. Astra is the first OpenAI model to cross the Critical cybersecurity threshold in the Preparedness Framework. Standard access refuses parts of that work outright. Rollout is staged: Daybreak enterprise customers first, then Plus, Pro, Business, Enterprise, the API and AWS. Pro, Business and Enterprise also get Astra Pro. OpenAI launched GPT-6 Astra today, September 3, 2026. At the press briefing, president Greg Brockman first conceded that AGI remains a “gray, fuzzy thing”, then went ahead anyway: “I think it’s not unreasonable to feel that we are now in the AGI era.” He closed with the same line: “Welcome to the AGI era.” ...

TL;DR: Gemini 3.8 Flash in 30 seconds Gemini 3.8 Flash landed on September 2, 2026, three weeks after 3.7 Flash. That is the third Flash release in three months. Price did not move: $0.75 input, $3.75 output per million tokens. The promo ends December 31, 2026, then it doubles. A second model shipped alongside it: Gemini 3.8 Flash Cyber, tuned for vulnerability discovery and locked behind the new Fairwind Program. The benchmark table is split. It tops the chart on finance, legal, long video and chart reasoning, and it trails Claude Opus 5 badly on long horizon terminal and computer use work. The model “works harder”: more reasoning steps, more iterative tool calls. Same sticker price, potentially a bigger bill. The Flash release cadence has stopped being funny. 3.6 Flash shipped on July 21, 3.7 Flash on August 13, and Gemini 3.8 Flash today, September 2, 2026. Three releases in three months. ...

Summary: Gemini 3.7 Flash in 30 Seconds Gemini 3.7 Flash landed on August 13, 2026, only three weeks after 3.6 Flash. Introductory pricing is $0.75 in / $3.75 out per 1M tokens: half of 3.6 Flash’s standard rate. The promo ends December 31, 2026. Coding jumped hard: FrontierCode 1.1 went from 34.4% to 43.6%, DeepSWE v1.1 from 48.6% to 65.3%. Context window is 1,048,576 tokens with a 65,536 token output cap. It takes text, images, video, audio and PDF. It is not the smartest model on the board: 56 on the Artificial Analysis index, one point behind GPT-5.6 Terra and Muse Spark 1.2, at roughly a third of their price. Google’s Flash line has never been about winning the intelligence crown. It is the model you run at volume: cheap enough to call thousands of times a day, fast enough to sit inside a product. Gemini 3.7 Flash stretches that definition. ...

On July 21, 2026, Google announced three new Gemini models at once: Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and the defense-focused Gemini 3.5 Flash Cyber. The theme of the announcement is clear: not higher scores, but getting the same job done with fewer tokens. As agentic workflows move into production, the bill is driven less by how smart a model is and more by how many tokens that intelligence burns. Google aimed straight at that. Here are the details. ...